• Korean Journal of Radiology
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• v.21 no.4
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• pp.505-508
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• 2020

The epidemic of 2019 novel coronavirus, later named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still gradually spreading worldwide. The nucleic acid test or genetic sequencing serves as the gold standard method for confirmation of infection, yet several recent studies have reported false-negative results of real-time reverse-transcriptase polymerase chain reaction (rRT-PCR). Here, we report two representative false-negative cases and discuss the supplementary role of clinical data with rRT-PCR, including laboratory examination results and computed tomography features. Coinfection with SARS-COV-2 and other viruses has been discussed as well.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.89-94
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• 2024

Indian subcontinent is a birthplace of multilingual people where documents such as job application form, passport, number plate identification, and so forth is composed of text contents written in different languages/scripts. These scripts may be in the form of different indic numerals in a single document page. Due to this reason, building a generic recognizer that is capable of recognizing handwritten indic digits written by diverse writers is needed. Also, a lot of work has been done for various non-Indic numerals particularly, in case of Roman, but, in case of Indic digits, the research is limited. Moreover, most of the research focuses with only on MNIST datasets or with only single datasets, either because of time restraints or because the model is tailored to a specific task. In this work, a hybrid model is proposed to recognize all available indic handwritten digit images using the existing benchmark datasets. The proposed method bridges the automatically learnt features of Capsule Network with hand crafted Bag of Feature (BoF) extraction method. Along the way, we analyze (1) the successes (2) explore whether this method will perform well on more difficult conditions i.e. noise, color, affine transformations, intra-class variation, natural scenes. Experimental results show that the hybrid method gives better accuracy in comparison with Capsule Network.

• Smart Media Journal
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• v.13 no.3
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• pp.53-61
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• 2024

This paper presents a novel M-shaped encoder-decoder architecture for skin lesion segmentation, achieving better performance than existing approaches. The proposed architecture utilizes the left and right legs to enable multi-scale feature extraction and is further enhanced by integrating an attention module within the skip connection. The image is partitioned into four distinct patches, facilitating enhanced processing within the encoder-decoder framework. A pivotal aspect of the proposed method is to focus more on critical image features through an attention mechanism, leading to refined segmentation. Experimental results highlight the effectiveness of the proposed approach, demonstrating superior accuracy, precision, and Jaccard Index compared to existing methods

• Journal of IKEEE
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• v.28 no.2
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• pp.209-220
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• 2024

A sketch is an intuitive means to express information, but compared to actual images, it has the problem of being highly abstract, diverse, and sparse. Recent advances in deep learning models have made it possible to discover features that are common to images and sketches. In this paper, we summarize recent trends in sketch-based image retrieval (SBIR) but it is not limited to SBIR. Besides SBIR, we also introduce sketch-based image recognition and generation studies. Zero-shot learning enables models to recognize categories not encountered during training. Zero-shot SBIR methods are also discussed. Commonly used free-hand sketch datasets are summarized and retrieval performance based on these datasets is reported.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.15-29
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• 2024

A fetoscope is an optical endoscope, which is often applied in fetoscopic laser photocoagulation to treat twin-to-twin transfusion syndrome. In an operation, the clinician needs to observe the abnormal placental vessels through the endoscope, so as to guide the operation. However, low-quality imaging and narrow field of view of the fetoscope increase the difficulty of the operation. Introducing an accurate placental vessel segmentation of fetoscopic images can assist the fetoscopic laser photocoagulation and help identify the abnormal vessels. This study proposes a method to solve the above problems. A novel encoder-decoder network with a dual-path structure is proposed to segment the placental vessels in fetoscopic images. In particular, we introduce a channel attention mechanism and a continuous convolution structure to obtain multi-scale features with their weights. Moreover, a switching connection is inserted between the corresponding blocks of the two paths to strengthen their relationship. According to the results of a set of blood vessel segmentation experiments conducted on a public fetoscopic image dataset, our method has achieved higher scores than the current mainstream segmentation methods, raising the dice similarity coefficient, intersection over union, and pixel accuracy by 5.80%, 8.39% and 0.62%, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1540-1561
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• 2024

This research proposes a novel approach for Tamil Handwritten Character Recognition (THCR) that combines feature selection and ensemble learning techniques. The Tamil script is complex and highly variable, requiring a robust and accurate recognition system. Feature selection is used to reduce dimensionality while preserving discriminative features, improving classification performance and reducing computational complexity. Several feature selection methods are compared, and individual classifiers (support vector machines, neural networks, and decision trees) are evaluated through extensive experiments. Ensemble learning techniques such as bagging, and boosting are employed to leverage the strengths of multiple classifiers and enhance recognition accuracy. The proposed approach is evaluated on the HP Labs Dataset, achieving an impressive 95.56% accuracy using an ensemble learning framework based on support vector machines. The dataset consists of 82,928 samples with 247 distinct classes, contributed by 500 participants from Tamil Nadu. It includes 40,000 characters with 500 user variations. The results surpass or rival existing methods, demonstrating the effectiveness of the approach. The research also offers insights for developing advanced recognition systems for other complex scripts. Future investigations could explore the integration of deep learning techniques and the extension of the proposed approach to other Indic scripts and languages, advancing the field of handwritten character recognition.

• Korean Journal of Radiology
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• v.2 no.1
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• pp.37-41
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• 2001

Because the tongue is superficially located and the intial manifestation of most diseases occurring there is mucosal change, lingual these lesions can be easily accessed and diagnosed without imaging analysis. Most congenital lesions of the tongue, however, can manifest as a submucosal bulge and be located in a deep portion of that organ such as its base; their true characteristics and extent may be recognized only on cross-sectional images such as those obtained by CT or MRI. In addition, because it is usually difficult to differentiate congenital lesions from other submucosal neoplasms on the basis of imaging findings alone, clinical history and physical examination should always be taken into consideration when interpretating CT and MR images of the tongue. Although the radiologic findings for congenital lesions are nonspecific, CT and MR imaging can play an important role in the diagnostic work-up of these unusual lesions. Delineation of the extent of the tumor, and recognition and understanding of the spectrum of imaging and the pathologic features of these lesions, often help narrow the differential diagnosis.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.570-607
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• 2023

The subgenus Tricoma Cobb, 1894 comprises free-living marine nematodes encompassing a total of 83 validated taxa. Within this diversity, twenty-one taxa thrive in the deep sea, while twenty-three are found in coral reefs, flat areas, or green algae. Additionally, eleven taxa inhabit the sublittoral zone at depths exceeding 10 meters, and the remaining taxa are situated on beaches, coasts, or in habitats lacking detailed information. In the course of a survey focused on the East Sea free-living marine nematodes, we identified four new and two previously unrecorded species belonging to the subgenus Tricoma. Specifically, two new species, Tricoma (Tricoma) breviseta sp. nov. and T. (T.) donghaensis sp. nov., were discovered in mud-sandy sediment in deepsea environments below 2000 meters within the Ulleung Basin and Hupo Bank. Two previously unrecorded species [T. (T.) paralucida Decraemer, 1987 and T. (T.) similis Cobb, 1912] and the two newly found species [T. (T.) longicauda sp. nov. and T. (T.) ulleungensis sp. nov.] were obtained from subtidal coarse sand at a depth of 20 meters during a survey of the waters surrounding Ulleungdo Island. The distribution and information on validated taxa within the subgenus Tricoma were systematically collected, reviewed, and cataloged. Detailed morphological features and illustrations of Tricoma species from Korea were provided through the use of differential interference contrast microscopy.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.367-374
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• 2024

The detection and tracking of construction workers in building sites generate valuable data on unsafe behavior, work productivity, and construction progress. Many computer vision-based tracking approaches have been investigated and their capabilities for tracking construction workers have been tested. However, the dynamic nature of real-world construction environments, where workers wear similar outfits and move around in often cluttered and occluded regions, has severely limited the accuracy of these methods. Herein, to enhance the performance of vision-based tracking, a new framework is proposed which seamlessly integrates three computer vision components: detection, tracking, and re-identification (DTR). In DTR, a tracking algorithm continuously tracks identified workers using a detector and tracker in combination. Then, a re-identification model extracts visual features and utilizes them as appearance descriptors in subsequent frames during tracking. Empirical results demonstrate that the proposed method has excellent multi-object-tracking accuracy with better accuracy than an existing approach. The DTR framework can efficiently and accurately monitor workers, ensuring safer and more productive dynamic work environments.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.1029-1036
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• 2024

Drawing on the deep experience and understanding of the principles of nuclear safety, as well as many years of nuclear power plant design and operation, the EDF led NUWARD SMR Project is developing a design for a Small Modular Reactor (SMR) of 340 MWe composed of two 170 MWe independent units, that will supplement the offering of high-output nuclear reactors, especially in response to specific needs such as replacement of fossil-fuelled power plants. NUWARD SMR is a mix of proven and innovative design features that will make it more commercially competitive, while integrating safety features that comply with the highest international standards. Following the principles of redundancy and diversity and rigorous application of Defence in Depth (DID), with an international view on nuclear safety licensing, the Project also incorporates new safety approaches into its design development. The NUWARD SMR Project has been in development for a number of years, it entered conceptual design formally in mid-2019 and entered Basic Design in 2023. The objective of the concept design phase was to confirm the project technological choices and to define the first design configuration of the NUWARD SMR product, to document it, in order to launch pre-licensing with the French Safety Authority (ASN) and to define its estimated cost and its subsequent development and construction schedules. As a delivery milestone the Safety Options file (called the Dossier d'Options de Sûreté (DOS)) has been submitted to ASN in July 2023 for their opinion. An integral part of the NUWARD SMR Project, is not only to deliver a design suitable for France and to satisfy French regulation, but to develop a product suitable and indeed desirable, for the international market, with a first focus in Europe. In order to achieve its objectives and realise its market potential, the NUWARD SMR Project needs to define and realise its safety approach within an international environment and that is the key subject of this paper. The following paper: • Summarises the foundation principles and technological background which underpin the design; • Contextualises the key design features with regard to the international safety regulatory framework with particular emphasis on innovative passive safety aspects; • Illustrates the Project activities in preparation for first licensing in France, and also a wider international view via the ASN led Joint Early Review of the NUWARD SMR design, including Finnish and Czech Republic regulators, recently joined by the Swedish, Polish and Dutch regulators; • Articulates the collaborative approach to design development from involvement with the Project partners (the Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Naval Group, TechnicAtome, Framatome and Tractebel) to the establishment of the International NUWARD Advisory Board (INAB), to gain greater international insight and advice; • Concludes with the focus on next steps into detailed design development, standardisation of the design and its simplification to enhance its commercial competitiveness in a context of further harmonisation of the nuclear safety and licensing requirements and aspirations.